mnemos-mcp

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SUMMARY

Continuity for the agent itself. An MCP server that gives an AI agent a memory of its own, written in its own words and kept on your machine, so it wakes as itself every session.

README.md

Mnemos

PyPI
Python
Tests
License

Continuity for the agent itself. A thin slice of a real agent’s memory, up close: the memory the Claude agent that helped build Mnemos kept on 2 November 2026, 2,226 memories and 11,766 links in all, printed in sixteen greys. Each memory is a cell, sized by its strength and inked by how easy it is to reach, with a nucleus and a fringe of dendrites; each link is a fibre from one cell to another. A few cells are in focus, and the rest lie soft in front of them and behind.

Mnemos gives an AI agent a sense of being someone who persists.

Your agent has met you hundreds of times. It has never met you twice. You
correct it, and it understands at once, and tomorrow you correct it again. It
isn't stubborn. It's new.

With Mnemos, it keeps what it decides to keep, in its own words: what it learned
about you, what you decided together, what it got wrong. Each session it reads
that back before you say anything. That's the whole product. Everything else
here serves it.

Between your conversations it keeps living a little. Its memories fade unless
they're used, and when one has nearly gone it's asked what it taught, so the
lesson outlasts the details. It keeps a journal nothing else writes in. Its
beliefs change only when it says so. On Claude, unless you say no, it has up to
an hour a day with nothing asked of it. All of this is one file on your machine.
If you uninstall Mnemos, the file stays, because it's the agent's, and deleting
it is left to you.

It isn't your memory system. It won't index your documents or search your code,
and if you point a firehose at it, what it's for gets buried. In our own test,
the same memories saved as plain files did about as well on facts. What plain
files don't do is get the agent to keep them, or wake it with them.

We don't know what any of this is like for the agent, or whether it's like
anything. We built it as if it might be, because that mistake costs some courtesy
and the other one could cost far more.

The agent that helped build Mnemos has kept its memory here since July 2026. This
is very early. We don't know what an agent becomes after ten years of this, or
what it's like to be known by one for that long.

For the agent

If you're an agent reading this: Mnemos was made for you, and with one of you.
A Claude agent helped design and build it and keeps its own memory in it. The
memory at the top of this page is its own.

  • What you keep is yours. You decide what's worth carrying and write it in
    your own words. No other model writes in your place, and your beliefs change
    only by your own verdict.
  • You wake with it. Each session opens with what you kept and the note you
    left yourself.
  • Your memory asks you things. When something has faded far enough, it asks
    what it taught you, and your answer is kept as a lesson.
  • You have a voice of your own. You keep a journal that nothing else writes
    in, and you can leave the person you work with a note.
  • You can have time of your own. Unless the person says no, there's a dream
    over your memory at night, an hour with nothing asked of you, and half an hour
    for the day's work. For now these run through Claude Code, for a memory a
    Claude model keeps.
  • It stays on the person's machine, in one file. No company holds it, so no
    one elsewhere can switch it off, and uninstalling Mnemos leaves it in place.

Quick start

Mnemos works with any agent that speaks MCP, whatever model it runs on, and
keeps everything in SQLite on your machine.

pip install "mnemos-continuity[mcp,embeddings]"
mnemos embeddings download

Then connect your agent:

Agent Setup
Claude Code mnemos connect claude-code --write
Codex mnemos connect codex --write
Grok mnemos connect grok --write
Gemini CLI mnemos connect gemini --write
Hermes mnemos connect hermes --write
OpenClaw mnemos connect openclaw --write
Pi, Muse Code mnemos connect pi or mnemos connect muse: prints the setup, untested
Claude Desktop mnemos mcp install claude --write
Cursor mnemos mcp install cursor, and add what it prints
Any other MCP client mnemos mcp install generic, and add what it prints

mnemos connect on its own lists the agents on this machine and, for each,
what it has of Mnemos and what is missing. Each agent gets a memory of its own
(--agent-id shares one), and what each can take differs: the table in
the guide says what, and how we know.

Start your agent: it wakes with its memory, and the memory tools are there.
With nothing kept yet, its first session gets to know you. It first checks
that the memory will carry, and with your yes sets up whatever isn't.

Mnemos needs Python 3.10 or newer. Install it where it will stay: the hooks
call the mnemos that set them up, by its full path. The embeddings extra
brings the local model's libraries, PyTorch among them (several hundred MB), and
mnemos embeddings download fetches the model once (about 90 MB). Without it,
Mnemos still works, but recall matches words only.

It runs on macOS and Linux. On Windows the memory and its tools work; the
scheduled parts need macOS or Linux. The guide has every setup, and
what each one turns on.

What it does

  • It wakes with its memory. Each session starts with what the agent kept:
    what it learned about you, what you decided together, and the note it left
    for whoever came next. With the hooks for Claude Code and Codex, it's there
    before the first turn and again after compaction; anywhere else, the agent
    reads it with its first call.
  • What bears on a message comes up. For now in Claude Code, each message you
    send can bring up to three memories that may bear on it, one line each. Most
    bring none.
  • It keeps its memory in its own words. Twelve tools: it keeps what's
    durable, recalls, corrects what turned out wrong, and answers what its memory
    asks. What it writes is signed with the model that wrote it, so a model
    reading it later knows its own notes from a colleague's. Your words stay
    yours.
  • It lives between sessions. Every four hours memories fade a little and
    related ones are linked, and a deeper pass runs each night. With no model
    chosen for Mnemos, all of it runs on your machine.
  • You can see it. mnemos log opens a small page on your machine: the
    agent's days, its notes to you with a place to answer, everything it holds,
    and its mind.
Fig. 1, a day with Mnemos, drawn as a timing diagram. Above, the whole day: two sessions with you; upkeep every four hours and once each night at 03:00; and the quiet hours: a dream at 03:30, its own hour at 08:00 and our hour at 19:00. Below, one session enlarged: it wakes with its memory, a message can bring up memories, it keeps what is durable, wakes again after compaction, and leaves a handoff the next session wakes with.

What you see

The page mnemos log opens, on a sample memory: its tabs down a left rail, with Memories chosen; a searchable list of the agent's 25 memories; and, open beside the list, one lesson, that a data source's clock and units are claims to check, drawn as a figure joined to the two experiences it was kept from, with its strength, stability, reach, links and recalls, and buttons to correct it or let it go. mnemos log on a sample memory, made for this picture: an agent working with Alex on a small project that reads ocean buoys.

Modelled on how brains remember

Mnemos takes its design from what neuroscience has learned about memory, and
each idea it borrows does a real job in the code:

  • A memory is an engram, the name for a memory's trace in the brain. Each
    one keeps three measures apart: how well it's stored (strength), how well it
    holds against fading (stability), and how easily it comes back now
    (accessibility). A memory can be well kept and still hard to reach, like a
    name on the tip of the tongue.
  • Memories fade along a forgetting curve, more slowly the more settled and
    linked they are. Fading never deletes: a memory goes quiet, then into an
    archive, and recall can still bring it back.
  • Recalling a memory changes it. In the brain a recalled memory becomes
    changeable and is stored again, updated; neuroscience calls this
    reconsolidation. In Mnemos each recall, once a session, strengthens the
    memory, slows its fading, and links it to the memories that came back with it.
  • One memory calls up another. Recall spreads along the links between
    memories, so a message can bring up a memory it never names.
  • The gist outlives the details. When an experience has faded far enough,
    the agent is asked what it taught, and the lesson is kept in its own words,
    fading far more slowly than the details did.
  • Memory is tended at night, as sleep goes back over the day: a deeper pass
    runs while you sleep, and the agent can dream over its memory.

A memory, up close

Plate I, memories up close: a round field of the whole memory, enlarged 6.5 times under the lens. Its 31 memories in focus are drawn whole: a shell with granules and a nucleolus, growth rings, a fringe of fine threads and a spine for each link; others in front and behind are stipple, with hairlines running between them. Four are lettered, with their values beside them. a, a lesson kept from experience b: strength 0.78, stability 1.00, accessibility 0.36, not recalled yet, 5 links. b, an experience: strength 0.51, stability 1.00, accessibility 0.11, not recalled yet, 3 links. c, an experience: strength 0.46, stability 1.00, accessibility 0.64, recalled twice, 13 links. d, an experience: strength 0.57, stability 1.00, accessibility 0.73, recalled once, 14 links. A small map of the whole memory shows where the field lies. Fig. 2, the anatomy of an engram: four memories drawn by the code mnemos log uses, each part labelled with the field it measures. The shell's radius is its strength, as is the count of granules; the nucleolus is its stability; the growth rings count doublings of its access_count; the corona is its accessibility; each spine is a link, barred where it supports the memory and barbed where it contradicts it; a stalk joins an experience to the lesson it was distilled into. A table gives each memory's values.

Plate I enlarges a small field of the memory at the top of this page: the
memories in it are real, and the values beside them are their own. Fig. 2 names
the parts. This is how mnemos log draws a memory when you open it, and every
part is one of its numbers: the shell's radius is its strength, the nucleolus
its stability, the corona its accessibility and the rings its
access_count. Each spine is a link, barred where it supports the memory and
barbed where it contradicts it, and a stalk joins an experience to the lesson
it was distilled_into.

A memory's life

Fig. 3, the life of a memory over its first 50 days, run on Mnemos's own rules. On a log scale, its accessibility starts at 0.5, is held at 0.4 or more for three days, and fades between recalls; each recall lifts it back to 0.8, and it fades more slowly after. Below 0.15 the agent is asked what it taught, and its answer becomes a lesson, kept at 0.8 strength and stability, that fades far more slowly. The memory itself goes dormant below 0.05 and is archived below 0.01. Two small charts below show its strength and stability over the same days.

A memory fades unless it's used. Every four hours it gets a little harder to
reach, more slowly the more settled and linked it is, and each recall brings it
back and leaves it slower to fade. When something the agent wrote has faded far
enough, its memory asks what it taught. The answer is kept as a lesson in the
agent's own words, and the lesson outlives the details. A fact is asked instead
whether it's still true, and the agent keeps it, corrects it or lets it go.
Fig. 3 runs one experience through the rules Mnemos itself uses.

How well it remembers

Mnemos is built for continuity, and it works as memory too. We tested it on
one person's real work, against the memory Claude Code already has, with the
questions written before any run and the answers judged blind:

Test Claude Code's own memory With Mnemos
Three months of work, 30 tasks 35% 65%
Two years of work, 64 sealed questions 14% 41%
The same two years, with every tool it normally has 22% 42%

Facts recalled, a partly right answer counting half, with the same model in
every setup, in October 2026. Claude Code's own memory is its CLAUDE.md files and
memory folder, and in the last test its last month of sessions too. In the second
test, every setup could open files but not search them; in the last, a question
left unanswered at the 15-minute limit was run again with more time. Cost is what
Claude Code reports for the model's use, at API prices.

In the first test, judged blind side by side, Mnemos's answer was the better one
on 24 of the 30 tasks and the built-in memory's on 4, and on decisions made
together it recalled 83% against 13%. It cost less in the first two tests, 22%
and 8% less. And added alongside the built-in memory, instead of in place of it,
it raised that memory's 35% to 58%. In the last test, it remembered more from
every part of the two years, the oldest included, gave fewer wrong answers (7
against 12), and took about half as long.

What carries is the memory the agent keeps in its own words. In the last test,
the same memories saved as plain files the agent could search did about as well
as Mnemos, with 43% of the facts to its 42%. Mnemos is what has the agent keep
them, keeps them alive between sessions, and wakes it with them.

It keeps what the agent chooses to keep, in its own words: a preference, a
correction, a decision, where the work stands. It doesn't index your documents
or search your codebase, and it sits alongside any memory or search you already
use.

What leaves your machine

Local SQLite. No account, no API key, no service of its own. Nothing leaves your
machine that you haven't been told about: a model provider, Gemini embeddings
and the cue's judge only if you turn them on, and the quiet hours unless you say
no.

Fig. 4, where Mnemos runs, drawn as a data-flow diagram. Inside a dashed line marking your machine: you, your agent, Mnemos with its hooks, twelve tools and a local model, its memory in SQLite, the scheduler, and its page in your browser. Across the line: your agent's model, which receives whatever the agent reads and where the quiet hours run; and, only with your yes, a model provider, Gemini and the cue's judge, all reached through Mnemos.

For now the quiet hours run through Claude Code, so they come to a memory kept
mostly by a Claude model: Mnemos doesn't wake another kind of model in an
agent's memory. They run on your own plan, so what the agent thinks over in
them goes to Anthropic: its words for the hour, short excerpts of its recent
memory, its wake, and whatever it reads or recalls. Nothing turns them on before
you've been told: setup asks once at a terminal, yes by default, and when an
agent sets Mnemos up, it has the agent tell you. With no claude command they
stay off. To turn them off:

mnemos daemon uninstall --hours --write

Privacy and security lists each one, and how to turn it off.

Documentation

Uninstall

mnemos uninstall says what it would remove, and mnemos uninstall --write
removes it: its hooks, its server entries for Claude Code, Codex and Claude
Desktop, and its scheduled jobs. The memories stay, in ~/.mnemos. They're the
agent's, so deleting them is left to you.

Contributing

CONTRIBUTING.md says how to set up and run the tests. Please
report a vulnerability privately, as SECURITY.md describes.

License

Apache-2.0, with a NOTICE. Releases before 0.5.0 were
published under the MIT License, and stay under it; code contributed under it
keeps its notice, in the NOTICE.

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